In ecommerce, Amazons and Wayfairs around the world have become masters of leveraging data to show the right product to the right customer at the right time.
Faced with declining headcount due to the COVID-19 pandemic, some healthcare organizations are turning to e-commerce strategies to improve their own staffing and planning processes – showing the right passage to the right worker per diem at the right time.
Whether it’s buying a couch online or browsing the available shifts, people will only tolerate scrolling on their phones for a while, so data science needs to offer users options that they are likely to sue.
The stakes are of course much higher in the field of health. If one consumer does not buy a sofa, another can; but if a shift is not staffed, a healthcare organization may not meet prescribed staffing ratios – and the quality of care may suffer.
Ike Nnah, Co-Founder and CTO at IntelyCare, a provider of staffing and healthcare planning technology, chats with IT health news the attractiveness of e-commerce strategies, how healthcare can use these strategies, the role of artificial intelligence and some examples of it all in action.
Q. Why would healthcare look to e-commerce for help with data science? What is the draw?
A. E-commerce has already undergone this digital transformation in which healthcare workers find themselves. The e-commerce space is teeming with talent, experience and knowledge that the healthcare staffing industry can tap into.
There are similarities between the world of e-commerce and the healthcare workforce, in how a consumer buys a product and how a healthcare provider chooses to change jobs. But there are also a lot of differences that need to be addressed.
For example, geography is essential for health workforce staffing, while e-commerce typically offers pricing at the national level. And the health worker product (quarters available) has a short shelf life, compared to products listed on sites like Wayfair or Amazon.
But, healthcare organizations can successfully adopt data science practices if they can harness the learnings of e-commerce models, apply them in a thoughtful way that takes into account their similarities, but tailors their operations to meet the needs of vendors. and facilities.
This does not apply to brick and mortar staffing agencies. This only matters to companies that let suppliers choose the shifts they want. When it is more of a buying experience for teams, ecommerce is a natural place to look for ideas.
As healthcare staffing becomes more digital and gives providers more freedom to choose which shifts they want to work on, the staffing experience is starting to look a lot like a staffing experience. shopping.
Only instead of buying books, suppliers choose the shifts. But the main differences are: Shifts are more fleeting than books or mattresses, and vendors only choose shifts from nearby facilities rather than a global catalog.
Q. What are some e-commerce data science strategies and practices that healthcare workers can leverage?
A. Personalization is one example. We know consumers live on their phones, and providers are no exception. They appreciate the ability to create their schedules and take shifts from their phones. It is easy and natural for them.
However, there are sometimes thousands of shifts to choose from, and they can’t see them all on their mobile device. Thus, health workers need to be selective about how they view changes. If the best shifts aren’t on the first page, vendors won’t see them.
Making team recommendations based on the parameters and behavior of a supplier can optimize the process of filling teams. This makes it much easier for establishments to fill shifts while providing a better experience for suppliers to find their perfect schedule.
Dynamic pricing provides the ability to frequently change prices, constantly tapping into all available purchase history data to achieve the best prices in the future.
While this happens all the time on e-commerce sites, it is not being used to its full potential in healthcare staffing. Dynamic pricing allows healthcare providers to raise the price of the hardest to fill shifts and lower the prices of the easiest to fill shifts, improving the odds of filling both shifts.
Ultimately, this strategy benefits the provider, the facility and the patient. Providers maximize their earning potential, facilities optimize their time, and in turn floors are well staffed and patients receive the care they deserve.
Q. Where does artificial intelligence come into play here? What role does he play?
A. As pricing and personalization algorithms become more sophisticated, they begin to enter the realm of true artificial intelligence. These algorithms can respond to patterns that businesses can ignore.
If designed correctly, these algorithms are basically another member of the team. They make business decisions like any employee, but limit themselves to decisions the company is comfortable with allowing them to make.
So, as long as the business creates appropriate limits for these algorithms, they can work for the business around the clock, they can be scalable, and they can generate positive results for a business and for the future of healthcare workers. .
Q. What are one or two examples of behavioral economics principles that can develop algorithms to more effectively “sell†finite, time-limited resources, such as shifts?
A. The first is loss aversion. In some cases instilling fear of losing something (like a product or turnover rate) can be more motivating than simply presenting good products, savings, or bonuses.
How you price something to a consumer is also extremely important. For example, you can advertise a shift at $ 16 per hour or promote it at $ 108 for the shift. While it’s the same payout, ultimately consumers react differently to their framing – so it’s critical to consider how you communicate a reward.
Finally, the timing of the promotion is very important. Data science can create hands-on exercises to determine what is most motivating for a consumer or, in this case, a supplier – the promise of larger future rewards versus smaller, instant rewards.
Twitter: @SiwickiHealthIT
Email the author: [email protected]
Healthcare IT News is a publication of HIMSS Media.
